Gemma 4 31B vs Kimi K2.6
Gemma 4 31B (2026) and Kimi K2.6 (2026) are agentic coding models from Google DeepMind and Moonshot AI. Gemma 4 31B ships a 256k-token context window, while Kimi K2.6 ships a 262K-token context window. On Google-Proof Q&A, Kimi K2.6 leads by 4.8 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Kimi K2.6 is safer overall; choose Gemma 4 31B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Gemma 4 31B | Kimi K2.6 |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Coding, RAG, and Agents |
| Context window | 256k | 262K |
| Cheapest output | - | $3.5/1M tokens |
| Provider routes | 0 tracked | 5 tracked |
| Shared benchmarks | 1 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Local decision data tags Gemma 4 31B for RAG, Agents, and Long context.
- Kimi K2.6 leads the largest shared benchmark signal on Google-Proof Q&A by 4.8 points.
- Kimi K2.6 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.6 has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2.6 uniquely exposes Vision, Reasoning, and Tool use in local model data.
- Local decision data tags Kimi K2.6 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemma 4 31B
Unavailable
No complete token price in local provider data
Kimi K2.6
$1,475
Cheapest tracked route: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 4 31B and Kimi K2.6; plan for SDK, billing, or endpoint changes.
- Kimi K2.6 adds Vision, Reasoning, and Tool use in local capability data.
- No overlapping tracked provider route is sourced for Kimi K2.6 and Gemma 4 31B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Reasoning, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-31 | 2026-04-20 |
| Context window | 256k | 262K |
| Parameters | 31B | 1T |
| Architecture | - | Mixture of Experts (MoE) |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Gemma 4 31B | Kimi K2.6 |
|---|---|---|
| Input price | - | $0.75/1M tokens |
| Output price | - | $3.5/1M tokens |
| Providers | - |
Capabilities
| Capability | Gemma 4 31B | Kimi K2.6 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | No | Yes |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
| Benchmark | Gemma 4 31B | Kimi K2.6 |
|---|---|---|
| Google-Proof Q&A | 85.7 | 90.5 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Gemma 4 31B at 85.7 and Kimi K2.6 at 90.5, with Kimi K2.6 ahead by 4.8 points. The largest visible gap is 4.8 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Kimi K2.6, reasoning mode: Kimi K2.6, and tool use: Kimi K2.6. Both models share multimodal input and function calling, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Gemma 4 31B has no token price sourced yet and Kimi K2.6 has $0.75/1M input tokens. Provider availability is 0 tracked routes versus 5. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 4 31B when provider fit are central to the workload. Choose Kimi K2.6 when coding workflow support, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemma 4 31B or Kimi K2.6?
Kimi K2.6 supports 262K tokens, while Gemma 4 31B supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 4 31B or Kimi K2.6 open source?
Gemma 4 31B is listed under Open Source. Kimi K2.6 is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemma 4 31B or Kimi K2.6?
Kimi K2.6 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemma 4 31B or Kimi K2.6?
Both Gemma 4 31B and Kimi K2.6 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for reasoning mode, Gemma 4 31B or Kimi K2.6?
Kimi K2.6 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 4 31B and Kimi K2.6?
Gemma 4 31B is available on the tracked providers still being sourced. Kimi K2.6 is available on NVIDIA NIM, Moonshot AI Kimi, Fireworks AI, OpenRouter, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.